Abstract #4520

Multimodal Correlation and Connectivity Analysis on Simultaneously Recorded MR-PET data

Ravichandran Rajkumar^1,2, Elena Rota Kops³, Jürgen Scheins⁴, Lutz Tellmann⁴, Christoph Lerche⁴, Karl-Josef Langen^4,5, Hans Herzog⁴, N. Jon Shah^4,6,7,8, and Irene Neuner^2,4

¹Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany, ²Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany, ³Forschungszentrum Juelich GmbH, Institute of Neuroscience and Medicine - 4, Jülich, Germany, ⁴Institute of Neuroscience and Medicine 4 (INM4), Forschungszentrum Jülich GmbH, Jülich, Germany, ⁵Department of Nuclear Medicine, RWTH Aachen University, Aachen, Germany, ⁶Institute of Neuroscience and Medicine 11, Forschungszentrum Jülich GmbH, Jülich, Germany, ⁷Department of Neurology, RWTH Aachen University, Aachen, Germany, ⁸Monash Biomedical Imaging, School of Psychological Sciences, Monash University, Melbourne, Australia

On a simultaneously recorded resting state MR-PET data, the functional connectivity metrics (namely ReHo, fALFF, and DC) from fMRI and the glucose metabolism from FDG – PET are calculated and correlated in the default mode network (DMN) regions of the brain. Results shows high connectivity of the DMN hubs is coupled with a high glucose consumption. Further investigations in patients are necessary to explore the potential of simultaneous imaging as a biomarker for disease staging, treatment response and monitoring

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